Page 113 - Hospital Authority Convention 2017

Parallel Sessions

PS2.3 Healthcare Financing 14:30 Theatre 1

Model Development for Population-based Resource Allocation
Zee B, Chong M, Yeoh EK
Division of Biostatistics, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong HOSPITAL AUTHORITY CONVENTION 2017
Kong

Introduction
The main aim of resource allocation is to drive efficiency and equity in healthcare provision, and to foster the goal of equity
between clusters in the long run as well to drive changes in the healthcare system without causing undesirable impact on
existing baseline services. In this presentation, we would introduce an analytical framework of a population-based resource
allocation model which is typically useful for addressing a number of specific issues encountered in Hong Kong.
Methodology
The model was developed with respect to six core services including acute inpatient, non-acute inpatient, special outpatient
clinic, primary care, accident and emergency, and allied health outpatient. The designated services, private services, and
other policy directed initiatives were taken out from the modeling process. We would show how the models with variables on
demographic, socio-economical, epidemiological, clinical, geographical, and other factors such as unmet needs and supply
were introduced and finally being incorporated. Two stage random effect models were being developed using data from
2011/12 to 2013/14 and then validated using data from 2014/15 and 2015/16.

Results
The model effects were highly significant and the correlation coefficients were in the range of 0.83-0.90 for all six core
services. The goodness-of-fit of the models was good in both the estimated amount of services from the model as well as the
total cost for each services after an average unit cost was used to carry out in the estimation. We have also developed the Tuesday, 16 May
methodology on assessing the impact of population mix, and the impact of cross-cluster flow.
Conclusions
The population-based resource allocation model is feasible and is shown to have high accuracy. Future applications can be
developed based on the model with good data and simulation of factors such as supply factor to help guide future healthcare
resource allocation and other policy decisions.

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